1. Emma Muir, Sam Muir, Jacob Sandlund, & David Smith Advisor: Dr. José Sánchez Co-Advisor: Dr. James Irwin

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3. 3 [1] Benign Malignant

4. Introduction How Ultrasound Works Coded Excitation Objective Motivation Significance Design Comparison 4

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6. 6 Conventional Ultrasound [2] Coded Excitation Ultrasound [2]

7. 7 Research Platforms Mostly single-element Large multi-element  RASMUS RASMUS [3]

8. 8 Ultrasound Research Platform Prototype  Arbitrary Waveforms o Coded excitation signals  Multi-element o Beamforming  Reduced size and cost Lecroy Oscilloscope

9. 9 Improve…  Ultrasound Techniques  Ultrasound Research Reduce size and cost

10. 10 Medical Applications  Detect and Diagnose Tumors  Noninvasive  Faster Results

11. 11 Previous Designs: Our Design: Digital Device Amplifier Transducer Digital Device Transducer Switching Amplifier D/A

12. 12 Oversample  1-bit  Densities represent voltages

13. 13 Transducer acts as a (BP) filter  Smooths / Averages

14. 14 Example:  0.5 V DC  -1 to 1 V Dynamic range 8-bit Two’s Complement (-128 to 127):  Value = 64 (0100 0000) Sigma Delta Modulation:  Oversample  1-bit

15. Introduction Functional Description Methods Results and Discussion Conclusion Questions 15

16. Introduction Functional Description Methods Results and Discussion Conclusion Questions 16

17. Up to 4 transducer channels Excitations <= 3 μs SNR > 50 dB 17

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19. 19 Generate Waveform

20. 20 Transmit Waveform

21. 21 Receive Image

22. 22 Create Image

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28. Time Gain Compensation (TGC)  Attenuation  TGC = Att * Depth * (Probe frequency)  white noise for larger depths 28

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30. Envelope Detection  Determines the bounds of the processed signal  Detects width and contains the display information  Absolute value of the Hilbert Transform 30

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32. Introduction Functional Description Methods Results and Discussion Conclusion Questions 32

33. Sigma Delta Modulation PC/FPGA Interface FPGA Data Processing  Pulse Compression  Delay Sum Beamforming 33

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35. 35 < 10% Mean Squared Error (MSE) 500 M samples/second Accuracy vs. Overloading (Saturation)  Order = 2nd  OSR = 16 o must be a power of 2 o 16*2 = 32 samples per period

36. 36 [4]

37. 37 [4]

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39. 39 [5]

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41. 41 Assign waveform to pins  Independent for each pin  (3 μs) * (500 MHz) = 1500 bits/waveform  1500 + 36 = 1536 bits/waveform (divisible by 512) Assign delay to pins  Increments of 4ns = (1/250 MHz)  250 MHz = memory clock rate of FPGA

42. 42 Transfer information for 4 pins in < 1 sec  <32 sec for 128 pins  (4 pins) * (1536 bits/waveform) sent within 1 sec  ~6 Kbps Start transmission

43. UART connection  115200 baud o Fastest FPGA baud rate  Sends as o 1 start bit o 8 data bits o 2 stop bits  (1536/8)*11*4 = 8448 bits  ~73 ms for 4 channels  ~2.3 s for 128 channels 43 Start Stop Data

44. 44

45. 45 Transmit at 500 MHz Output waveforms in parallel  4 individualized waveforms  Length of 3  s per waveform  1536-bits per waveform

46. 46 Yes No

47. 47 Transmit at 500 MHz  Two 250 MHz clock edges (transmits on rising and falling edge)  250 MHz * 2 = 500 MHz XOR

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49. Data Processing  Less than 2 minutes Display an image  Depths between 0.25 cm and 30 cm  Dynamic range between 40 dB and 60 dB 49

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51. Restore the spatial resolution Match reflected wave to original excitation Use Wiener filter  Optimal solution between a match filter and an inverse filter [6]  Solution determined by o Smoothing Factor (SF) o Predicted signal-to-noise-ratio (SNR) Predict SNR = 50 dB 51

52. Matched filter  Cross correlation of original coded excitation and received signal  Creates side lobes  Does not amplify noise  Optimal for large noise – small SNR Inverse filter  Inverse of the original coded excitation  No side lobes  Amplifies noise  Optimal for no noise – large SNR 52

53. 53 Wiener Filter Equation = Coded Excitation = Smoothing Factor = SNR of system Noise increases SNR decreases λ/S increases Closer to a Match Filter Noise decreases SNR increases λ/S decreases Closer to an Inverse Filter [1]

54. 54 SNR = 60 dB

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56. 56 128 Sensor Array Transducer Focal Point Narrowest beam Greatest amplitude Beamforming not necessary at this point 20 mm 4 mm 38.36 mm

57. 57 Amplitude at Point = Σ i=1 S i ( Depth + Delay(S i,Point)) [7] Delay(S,P) = (D SP - D SF )/c [7] S = sensor P = point D SP = distance from sensor to point D SF = distance from sensor to point c = 1540m/s (speed of sound in tissue) 8 Sensors Focal Point Point Depth

58. Introduction Functional Description Methods Results and Discussion Conclusion Questions 58

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65. 65 1.34% MSE

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67. Correlations Filtered Sigma-delta Modulated Linear Chirp Filtered Captured Data Filtered Linear Chirp 99.84%99.33% Filtered Sigma-delta Modulated Linear Chirp --------99.53% 67

68. Correlations Filtered Sigma-delta Modulated Linear Chirp Filtered Captured Data Filtered Linear Chirp 99.84%99.33% Filtered Sigma-delta Modulated Linear Chirp --------99.53% 68

69. Correlations Filtered Sigma-delta Modulated Linear Chirp Filtered Captured Data Filtered Linear Chirp 99.84%99.33% Filtered Sigma-delta Modulated Linear Chirp --------99.53% 69

70. Correlations Filtered Sigma-delta Modulated Linear Chirp Filtered Captured Data Filtered Linear Chirp 99.84%99.33% Filtered Sigma-delta Modulated Linear Chirp --------99.53% 70

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73. 73 h 1 (n) * c 1 (n) = h 2 (n) * c 2 (n)

74. 74 Field II Software [8] 10 mm separation 46 dB SNR 10 20 30405060708090 10 20 -10 -20 0 Distance in mm 100 Transducer

75. 75 Without BeamformingWith Beamforming

76. 76 REC Excitation and Pulse Compression Impulse Excitation

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78. Introduction Functional Description Methods Results and Discussion Conclusion Questions 78

79. Valid waveform transmission Portable system Multi-channel Research potential 79 Lecroy Oscilloscope

80. The authors would like to thank Analog Devices and Texas instruments for their donation of parts. This work is partially supported by a grant from Bradley University (13 26 154 REC) Dr. Lu Mr. Mattus Mr. Schmidt Andy Fouts 80

81. [1] J. R. Sanchez et al., "A Novel Coded Excitation Scheme to Improve Spatial and Contrast Resolution of Quantitative Ultrasound Imaging," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 56, no. 10, pp. 2111-2123, October 2009. [2] "Clinical Image Library." GE Healthcare-. GE Healthcare. Web. 14 Apr. 2011. [3] J. A. Jensen et al., “Ultrasound Research Scanner for Real-time Synthetic Aperture Data Acquisition,” IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 52, no. 5, pp. 881–891, 2005. [4] R. Schreier and G. C. Temes. Understanding Delta-Sigma Data Converters, John Wiley & Sons, Inc., 2005. [5] R. Schreier, The Delta-Sigma Toolbox Version 7.3. Analog Devices, Inc, 2009. 81

82. [6] T. Misaridis and J. A. Jensen, “Use of Modulated Excitation Signals in Medical Ultrasound Part I: Basic Concepts and Expected Benefits,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 52, no. 2, pp. 177-191, February 2005. [7] Thomeniu, Kai E. "Evolution of Ultrasound Beamformers." IEEE Ultrasonics Symposium (1996): 1615-622. Print. [8] J.A. Jensen. Field: A Program for Simulating Ultrasound Systems, Medical & Biological Engineering & Computing, pp. 351-353, Volume 34, Supplement 1, Part 1, 1996. 82

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